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By Pinakpani Pal

This quantity includes the newest within the sequence of ICAPR court cases at the state of the art of alternative points of development popularity. those meetings have already carved out a special place between occasions attended by way of the development popularity neighborhood. The contributions take on open difficulties within the vintage fields of picture and video processing, rfile research and multimedia item retrieval in addition to extra complicated subject matters in biometrics speech and sign research. a number of the papers concentration either on conception and alertness pushed simple examine development attractiveness.

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Extra info for Advances in Pattern Recognition: Proceedings of the Sixth International Conference, Indian Statistical Institute, Kolkata, India 2-4 January 2007

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Generic formalizations of spatial concepts were also developed and specified in different fields, for spatial reasoning in artificial intelligence, for Geographic Information Systems, etc. In a parallel domain, well formalized theories for image processing and recognition appeared in the image and computer vision community. Noticeably, both types of developments still remain quite disjoint and very few approaches try to use the abstract formalizations to guide image in- terpretation. The main reason is to be found in the so called "semantic gap", expressing the difficulty to link abstract concepts with image features.

They can be further revised or specified according to the visual features extracted from the image and matched with the symbolic representation. Using fuzzy representations, it is possible to deal with such cases, for instance by enlarging the areas where an object can be found, which amounts to relax the definition of the fuzzy relation. In summary, fuzzy representations have several To conclude this presentation, we summarize ongoing developments carried out in our team, towards the construction of a spatial relation ontology enhanced with fuzzy representations and its use for image interpretation.

U. Straccia, A fuzzy description logic for the semantic web, in Fuzzy Logic and the Semantic Web, ed. E. SanchezCapturing Intelligence (Elsevier, 2006) pp. 73-90. 51. C. Rosse and J. L. V. Mejino, Journal of Biomedical Informatics 36, 478 (2003). 25 52. J. Atif, C. Hudelot, I. Bloch and E. Angelini, From Generic Knowledge to Specific Reasoning for Medical Image Interpretation using Graph-based Representations, in International Joint Conference on Artificial Intelligence IJCAI'07, (Hyderabad, India, 2007).

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